Smart Voice-Activated Assistants Applications | Key Predictions
Dr. Evangelo Damigos; PhD | Head of Digital Futures Research Desk
- Sustainable Growth and Tech Trends
- Emerging Technologies
Publication | Update: Sep 2020
According to Ross Barrows, Head of Citi’s Australian Small Cap Research Team, the following applications of Smart Assistants are driving their increasing use:
Smart Speakers and TVs
Smart Assistants have resulted in speakers transforming from an audio device to devices that can answer questions as well as complete tasks. Smart speaker shipments are expected to grow at a 35% compound annual growth rate from 32 million units in 2017 to 142 million units in 2022 which includes doubling from 2019–22.
Another indicator of the increasing use of smart speakers is the number of skills being added to Amazon’s Echo and Alexa.
ComScore estimates that 50% of all searches will be by voice by 2020.
Navigation & Automotive
Another application of voice activated assistants is in the automotive industry. Driving presents a natural setting for the application of voice-based systems given that both hands and eyes are usually occupied.
Places Where People Use Voice Assistants
According to Clear Bridge Mobile research, the main driver of the shift towards voice user interfaces is the changing user demands. There is an increased overall awareness and a higher level of comfort demonstrated specifically by millennial consumers. In this ever-evolving digital world where speed, efficiency, and convenience are constantly being optimized.
The mass adoption of artificial intelligence in users’ everyday lives is also fueling the shift towards voice applications. The number of IoT devices such as smart thermostats, appliances, and speakers are giving voice assistants more utility in a connected user’s life. Smart speakers are the number one way we are seeing voice being used, however, it only starts there. Many industry experts even predict that nearly every application will integrate voice technology in some way in the next 5 years.
Key Predictions for Voice in 2020
Both Google and Amazon recently announced that both assistants will no longer require the use of repeated “wake” words. Previously both assistants were dependent on a wake word (Alexa or Ok, Google) to initiate a new line of conversation. For example, one would have to ask “Alexa, what’s the current temperature at the hallway thermostat?” and then have to say, “Alexa” again before requesting that the voice assistant to “set the hallway thermostat to 23 degrees.” It would be more convenient and natural for the user to say, “Alexa, what’s the current temperature at the hallway thermostat?” and then simply say “set my hallway thermostat to 23 degrees,” without requiring the wake word again, and now that’s possible.
Consumers use voice assistants in specific locations, usually while multitasking, and can either be alone or amongst a group of people when using them. Having devices that can decipher these contextual factors make a conversation more convenient and efficient with these devices, but it also shows that developers behind the technology are aiming to provide a more user-centric experience.
Search Behaviors Will Change
Voice search has been a hot topic of discussion. Visibility of voice will undoubtedly be a challenge. This is because the visual interface with voice assistants is missing. Users simply cannot see or touch a voice interface unless it is connected to the Alexa or Google Assistant app. Search behaviors, in turn, will see a big change. In fact, if tech research firm Juniper Research is correct, voice-based ad revenue could reach $ 19 billion by 2022, thanks in large part to the growth of voice search apps on mobile devices.
Brands are now experiencing a shift in which touchpoints are transforming to listening points, and organic search will be the main way in which brands have visibility. comScore data even reveals that 50% of all search will be via voice tech by 2020.
As voice search grows in popularity, advertising agencies and marketers expect Google and Amazon will open their platforms to additional forms of paid messages.
Voice assistants will also continue to offer more individualized experiences as they get better at differentiating between voices. Google Home is able to support up to six user accounts and detect unique voices, which allows Google Home users to customize many features. Users can ask “What’s on my calendar today?” or “tell me about my day?” and the assistant will dictate commute times, weather, and news information for individual users. It also includes features such as nicknames, work locations, payment information, and linked accounts such as Google Play, Spotify, and Netflix. Similarly, for those using Alexa, simply saying “learn my voice” will allow users to create separate voice profiles so the technology can detect who is speaking for more individualized experiences.
Voice Push Notifications
We’ve previously discussed the method of using user-centric push notifications as a means to re-engage users with your app, voice technology presents a unique means of distributing push notifications. As a way to increase user engagement and retention, push notifications simply remind users of the app and display relevant messaging to the user. Now that both Google Assistant and Amazon’s Alexa allow the user to enable spoken notifications for any third-party app that has the compatibility, users can hear notifications rather than read them. These notifications are generally related to calendar appointments or new content from core features.
CES 2019 continued to prove that voice and visual displays are merging into one seamless experience. This year Google showcased what is being called the E Ink screen. This display can show the weather, local traffic information, or calendar events. The push to bring visual and voice capabilities together allow users to further interact with the assistant.
Security Will Be a Focus
Forty-one percent of voice assistant users are concerned about trust and privacy according to a report from Microsoft. With news from Google I/O and Amazon’s re:MARS conferences announcing that assistants will essentially be able to plan an entire evening, for example, find local movie times, buy tickets, book a restaurant reservation and schedule an Uber, concerns regarding payments and sensitive information are valid. Voice payments, in particular, will become more secure and convenient for users to make purchases. Speaker verification and ID will also become paramount as part of the voice assistant experience with more security being built around the user.
Objectives and Study Scope
This study has assimilated knowledge and insight from business and subject-matter experts, and from a broad spectrum of market initiatives. Building on this research, the objectives of this market research report is to provide actionable intelligence on opportunities alongside the market size of various segments, as well as fact-based information on key factors influencing the market- growth drivers, industry-specific challenges and other critical issues in terms of detailed analysis and impact.
The report in its entirety provides a comprehensive overview of the current global condition, as well as notable opportunities and challenges.
The analysis reflects market size, latest trends, growth drivers, threats, opportunities, as well as key market segments. The study addresses market dynamics in several geographic segments along with market analysis for the current market environment and future scenario over the forecast period.
The report also segments the market into various categories based on the product, end user, application, type, and region.
The report also studies various growth drivers and restraints impacting the market, plus a comprehensive market and vendor landscape in addition to a SWOT analysis of the key players. This analysis also examines the competitive landscape within each market. Market factors are assessed by examining barriers to entry and market opportunities. Strategies adopted by key players including recent developments, new product launches, merger and acquisitions, and other insightful updates are provided.
Research Process & Methodology
We leverage extensive primary research, our contact database, knowledge of companies and industry relationships, patent and academic journal searches, and Institutes and University associate links to frame a strong visibility in the markets and technologies we cover.
We draw on available data sources and methods to profile developments. We use computerised data mining methods and analytical techniques, including cluster and regression modelling, to identify patterns from publicly available online information on enterprise web sites.
Historical, qualitative and quantitative information is obtained principally from confidential and proprietary sources, professional network, annual reports, investor relationship presentations, and expert interviews, about key factors, such as recent trends in industry performance and identify factors underlying those trends - drivers, restraints, opportunities, and challenges influencing the growth of the market, for both, the supply and demand sides.
In addition to our own desk research, various secondary sources, such as Hoovers, Dun & Bradstreet, Bloomberg BusinessWeek, Statista, are referred to identify key players in the industry, supply chain and market size, percentage shares, splits, and breakdowns into segments and subsegments with respect to individual growth trends, prospects, and contribution to the total market.
Research Portfolio Sources:
Global Business Reviews, Research Papers, Commentary & Strategy Reports
M&A and Risk Management | Regulation
The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.
Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:
As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.
Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.
Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pretax revenue and its total boughtin costs (costs excluding wages and salaries).
Forecasts of GDP growth: GDP = CN+IN+GS+NEX
GDP growth estimates take into account:
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.
Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.
Industry Life Cycle Market Phase
Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:
The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.
The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.
Forecasts of GDP growth per capita based on these factors can then be combined with demographic projections to give forecasts for overall GDP growth.
Wherever possible, publicly available data from ofﬁcial sources are used for the latest available year. Qualitative indicators are normalised (on the basis of: Normalised x = (x - Min(x)) / (Max(x) - Min(x)) where Min(x) and Max(x) are, the lowest and highest values for any given indicator respectively) and then aggregated across categories to enable an overall comparison. The normalised value is then transformed into a positive number on a scale of 0 to 100. The weighting assigned to each indicator can be changed to reﬂect different assumptions about their relative importance.
The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.
Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.
Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.